Inside the Playbooks of Top Brands
Explore how Amazon, Myntra and other industry leaders are leveraging AI to drive growth, efficiency, and innovation. Learn the strategies you can apply to your business.
How Myntra Uses AI to Dominate Fashion E-commerce & How Small Businesses Can Replicate It
AI: The Secret Sauce Behind Myntra’s Success
How Ant Financial Scaled Trust (Not Just Tech) : A Practical AI Lesson for MSMEs
If you run a small business in India, you’ve probably felt this:
Endless paperwork.
Repetitive tasks.
Chasing invoices.
Feeling like your business can’t grow unless you clone yourself 10 times.
Meanwhile, giants like Ant Financial are serving millions of customers with near zero delay. How?
It’s not just about size. It’s about systems.
And the right use of AI can help you scale without burnout or bloated teams.
They designed a new kind of AI-powered operating model, the one that removed the friction, not the humans.
Netflix Style AI Personalization for E-Commerce: Boost Sales & Conversions
What Netflix Knows About You and How E-Commerce Can Use the Same AI Tricks to Explode Sales
Netflix doesn’t care what you say you want. It watches what you do and it’s almost always right. It learned everything from your clicks, your pauses, your guilty pleasures at 2 AM. Now ask yourself: Why isn’t your
E-Commerce site doing the same?
Netflix isn’t just showing you movies. Behind every binge-worthy night is a masterclass in personalization, prediction, and psychological precision. Let’s apply these techniques in E-commerce.
Case Study on Myntra
How Myntra Uses AI to Dominate Fashion E-commerce & How Small Businesses Can Replicate It
AI: The Secret Sauce Behind Myntra’s Success
Myntra, a leading fashion e-commerce platform in India, has carved a niche in the highly competitive online shopping landscape. Owned by Walmart-backed Flipkart, it competes fiercely with Amazon Fashion, Reliance Ajio, and Tata Cliq in India’s booming fashion e-commerce market, expected to reach $35 billion by 2028.
In 2023, Myntra recorded 75 million new app users, doubling its customer base year over year. This massive growth, along with record-breaking conversions and customer satisfaction, is largely driven by its AI-powered innovations.
But here’s the big question: Can a small business build similar AI-powered features without spending millions? The answer is a resounding YES!
Imagine running a fashion business where customers can try on makeup virtually, receive personalized recommendations tailored to their tastes, and get deliveries optimized by AI-powered logistics—all without stepping into a store. Sounds futuristic? Myntra is already doing this today.
Myntra has also strategically expanded its presence across India, tailoring experiences based on regional audiences. A key move was acquiring Jabong to strengthen its foothold in the Indian market.
This case study explores the challenges Myntra faced, how it overcame them using AI, and how small and medium-sized businesses can leverage AI affordably and with minimal complexity.
Is It Worth Owning an E-commerce Fashion Brand in 2025?
The fashion e-commerce market has seen strong growth in recent years, increasing from $888.56 billion in 2024 to $974.87 billion in 2025 at a CAGR of 9.7%. This growth is fueled by rising disposable incomes, increased internet penetration, and the widespread adoption of online payments.
Looking ahead, the market is expected to reach $1,505.09 billion by 2029 at a CAGR of 11.5%. Key trends shaping this growth include AI-powered virtual assistants, augmented reality (AR) experiences, and the rising demand for sustainable fashion.
Myntra’s Financial Trajectory: Growth vs. Challenges
Myntra’s rapid expansion has led to significant revenue growth but also rising costs:
- Revenue surged 25%, from ₹3,501 crore in FY22 to ₹4,375 crore in FY23.
- Losses widened by 31%, from ₹598 crore to ₹782 crore, mainly due to higher operational expenses.
While Myntra is expanding its market presence, sustaining profitability remains a challenge in India’s price-sensitive market.
Should You Integrate AI Into Your Fashion Brand?
AI is reshaping the fashion industry:
- Generative AI could add $150 to $275 billion in profits.
- The global AI-in-fashion market is projected to reach $4.4 billion by 2027.
If this inspires you, let’s explore how you can achieve remarkable results using AI in fashion.
What Challenges Forced Myntra to Adopt AI?
Like any major e-commerce player, Myntra faced several challenges:
- High return rates due to customers being unsure how products would look on them.
- Limited personalization, forcing users to browse endlessly to find what they liked.
- High logistics costs due to inefficient delivery planning.
- Decision fatigue, making it hard for users to choose the right fashion products.
Problem Statement:
How can we help users make confident purchase decisions while reducing their cognitive load, and at the same time optimize logistics for timely delivery?
To tackle these challenges, Myntra turned to cutting-edge AI solutions. Let’s break down how.
Solving the High Return Rate Problem: Virtual Try-On
Virtual Try - On feature
Myntra currently uses virtual try-on technology for makeup products, allowing customers to see how items look before purchasing.
At present, Myntra only applies this technology to makeup. However, this tech is not limited to makeup and can be extended to clothing and other accessories.
How Myntra Uses It: Customers can either upload their picture or scan their face in real time, and AI shows them how a product will look on them, reducing returns.
Online shopping isn’t always a solo experience. Many users seek advice from friends before making a purchase—whether by sending a screenshot or sharing a product link. Recognizing this, Myntra introduced a ‘Share’ button, allowing users to instantly send product links to their frequent chats without leaving the app.
Instead of just sharing an image, the link includes a subtle nudge encouraging friends to try out the feature themselves. A clever way to drive organic growth!
Technology behind it: This technology typically employs a combination of Artificial Intelligence (AI), Augmented Reality (AR), and Computer Vision
How a General Virtual Try-On Technology is Built?
- Detection & Overlay:
- Computer Vision identifies the user’s face/body.
- AR & 3D rendering overlay digital products (clothing, makeup, etc.).
- Real-Time Tracking & Adjustments:
- AI ensures the virtual item moves naturally as the user moves.
- Pose Estimation (e.g., OpenPose, MediaPipe) accurately maps virtual products.
- 3D Clothing Simulation:
- Tools like Clo3D & Blender create lifelike fabric behavior (draping, folding).
- Augmented Reality (AR) Frameworks:
- WebAR, Spark AR, Lens Studio enable browser/mobile-based virtual try-ons.
- Face & Body Tracking SDKs:
- Face AR SDK, Banuba, DeepAR detect and track real-time movements for immersion.
WebAR allows instant virtual try-ons without requiring an app download.
Building virtual try-ons for makeup, spectacles, and jewelry is easier compared to clothing and shoes, which require 3D models. While 2D overlays can be used, they lack the realistic depth and fit of 3D simulations.
🔥 How Your Brand Can Do It:
- No-Code Solution: Use DeepAR (a virtual try-on SaaS) or Hugging Face’s AI Models to enable try-on features and build an MVP for testing.
- Another WebAR Option: Vossle is another platform you can use.
- With Code Option: Build a virtual try-on using Python + OpenCV + TensorFlow with pre-trained AI models.
Myntra partnered with ModiFace to bring AI-powered beauty try-ons, leading to a 1.5X increase in product consideration and 2X conversions in the beauty category.
Conversions has been increased using AI – Powered Personalisation
How Myntra Uses It: AI recommends products based on browsing history, past purchases, and style preferences.
Mystylist, Myntra’s AI feature, delivers better product suggestions by understanding user needs, past purchases, and style preferences in natural language.
Myntra’s MyFashionGPT (powered by ChatGPT) allows users to type natural queries like “What to wear for a wedding in Jaipur?” and receive AI-powered fashion recommendations instantly.
This feature represents an advanced AI-powered search integrated with ChatGPT, enhancing the shopping experience.
41% of shoppers buy from a different product category than what they started searching.
How Your Brand Can Do It Too:
- No-Code Solution: Use Clerk.io or Algolia Recommend for AI-powered suggestions.
- With Code Option: Train a recommendation model using Google’s TensorFlow Recommenders (TFRS).
- AI-driven chatbots assist shoppers in product discovery, reducing choice overload and improving the checkout process.
- Fit Prediction Tools: Solutions like True Fit use AI to recommend the right sizes, reducing return rates and enhancing customer satisfaction.
AI Helps in Cutting Costs by Optimised Delivery Planning in Logistics
How Myntra Uses It: AI predicts demand & optimizes delivery routes, reducing delays and cutting costs.
- AI-Driven Returns System: Myntra developed ‘Sabre’, an AI-based system that enables faster refunds for trustworthy customers and detects fraudulent return attempts.
- Return Trends in Fashion: Returns are common in fashion due to size and style variations, making efficient return policies crucial.
- Fraud Detection: Large retailers like Myntra leverage extensive data to train machine learning models that differentiate genuine returns from fraudulent activities.
- Reducing Return to Origin (RTO): AI predicts potential RTO cases (e.g., COD orders failing due to customer unavailability), enabling targeted customer interventions.
Operations (Predictive Insights & Automation)
- AI in Retail Analytics: AI generates real-time insights, detects supply chain risks, and optimizes inventory and pricing.
- Marketing Automation: AI automates campaign execution, such as setting up promotions and optimizing sales strategies with minimal manual effort.
🔥 How Your Brand Can Do It Too:
- No-Code Solution: Use Shiprocket’s AI-driven logistics platform for smart shipping.
- You can leverage a mix of no-code tools like Google AutoML, H2O.ai, or DataRobot to predict demand.
- For delivery route optimization, use Google Maps API, OptaPlanner, or Zeo Route Planner to reduce delays, cut costs, and improve efficiency.
Myntra’s M-Express service promises 24-48 hour delivery by leveraging AI to prioritize fulfillment efficiency.
AI-Driven Product Design for Faster & More Profitable Fashion Lines
How Myntra Uses It: Its RAPID AI system accelerates fashion design, slashing production time from 180 days to just 45 days!
How did this major transformation happen? Previously, designers relied on text-based instructions to create new designs. Now, thanks to generative AI, designers can instantly visualize concepts and refine them with ease.
Contrary to popular belief, Myntra didn’t jump on the AI bandwagon recently—it has been leveraging machine-generated designs since 2017, strategically keeping this innovation under wraps.
How Your Brand Can Do It Too:
- Low-Code Solution: Use AI-driven design platforms like Vue.ai to generate personalized clothing recommendations.
Additionally, tools like Resleeve.ai and CLO 3D can help streamline the design process. - Custom AI: Implement GANs (Generative Adversarial Networks) to create machine-generated designs based on emerging trends.
Myntra’s AI-designed Fast Fashion brands Moda Rapido & Here & Now generate Rs. 12-13 crore per month, proving AI can revolutionize fashion design.
AI-Generated Visuals & Product Imaging in Design
- Generative AI in Fashion: AI is transforming product design, 3D imaging, and campaign visuals, with projections that 20% of digital commerce imagery will be AI-generated by 2025.
- AI-Driven Visuals: AI can dynamically alter product images to match seasons or customer preferences, enhancing the overall shopping experience.
So, No More Designers Needed?
This is exciting news for fashion companies—they no longer need to hire large teams of designers, as AI can handle most of the basic design work.
However, for higher-level decision-making and creative refinement, experienced designers will still be highly valued.
The Myntra Effect
Myntra’s success isn’t just about selling fashion—it’s about how people shop.
By integrating seamless social sharing, understanding changing consumer behaviors, and expanding its market footprint, Myntra has built an engaging and ever-evolving shopping experience.
However, the challenge remains: Can Myntra balance growth with profitability in an industry known for high return rates and price-sensitive customers?
One thing is certain—Myntra isn’t just following fashion trends; it’s shaping them.
AI Isn’t Just for Big Companies
Most small business owners believe AI is too expensive or too complex. But that’s not true anymore!
Thanks to No-Code & Low-Code AI tools, any small business can implement AI without hiring a full tech team.
If you can automate product recommendations, improve trust, and optimize delivery – you can 10x your sales like Myntra.
Your Business AI Playbook 📖
1️⃣ Start with a No-Code AI tool: Use DeepAR for virtual try-on or Clerk.io for AI-powered search recommendations.
2️⃣ Optimize logistics with AI: Use Shiprocket AI for automated shipping solutions.
3️⃣ Explore AI for marketing & design: Leverage ChatGPT, Copy.ai for product descriptions, and AI tools like CLO 3D for design generation.
4️⃣ Gradually explore Low-Code solutions: Focus on customization & scalability as your business grows.
Make AI Work for Your Business Today!
AI is no longer a luxury—it’s a necessity.
The businesses that embrace it will dominate, while others will struggle to keep up.
Want help in setting up AI for your business? Start today by exploring the No-Code & Low-Code tools mentioned here.
If Myntra can do it at scale, so can you!
Case Study on Ant Financials
How Ant Financial Scaled Trust (Not Just Tech) : A Practical AI Lesson for MSMEs
Don’t Remove People , Remove Friction:
Why is everything still manual?
If you run a small business in India, you’ve probably felt this:
Endless paperwork.
Repetitive tasks.
Chasing invoices.
Manually approving every loan, order or payment.
Feeling like your business can’t grow unless you clone yourself 10 times.
And the worst part? You’re working harder than ever but it still feels like you’re falling behind.
Most small business owners whether running a shop, a consultancy or a manufacturing unit are drowning in routine work.
Meanwhile, giants like Ant Financial are serving millions of customers with near zero delay. How?
It’s not just about size. It’s about systems,
and the right use of AI can help you scale without burnout or bloated teams.
They designed a new kind of AI-powered operating model, one that removed the friction, not the humans.
Let’s look at how Ant Financial did it in a bit more detail and more importantly, what you can take away from it.
Chapter 1: Ant Financial : What They Solved First
Back in the early 2010s, people in China didn’t fully trust online payments. Alibaba (Ant’s parent company) realized that without trust, online transactions would stay small.
So they built Alipay: a simple digital wallet that held money in escrow until both parties confirmed the deal. This wasn’t just a payment tool ,it was a digital substitute for human trust.
And from there, they did something people often dream of but rarely pull off:
• Served 700 million+ users and 10+ million SMEs.
• Processed microloans in seconds.
• Reached millions of small merchants with just a QR code.
• Created a financial ecosystem touching payments, lending, insurance and investment.
And at the center of this scale wasn’t just a brilliant business model, it was a frictionless digital operating system powered by AI.
By 2018, Ant Financial had become the most valuable fintech company in the world, valued at $150 billion more than Goldman Sachs or American Express.
Chapter 2: The Real Power Move : Using AI to Remove Friction, Not People
It’s easy to think, “They just used AI to replace humans.”
But that’s not what happened.
“Let me be clear, the goal isn’t to fire people. It’s to unburden them.”
Your team shouldn’t be stuck chasing invoices, sorting spreadsheets or repeating the same task 50 times a week. That’s where AI shines.
They built systems that:
• Handled approvals instantly
• Flagged fraud automatically
• Scored credit using behavioral data
• Learned from every transaction
Ant didn’t fire humans.They freed them and so their energy could go toward strategy, design and growth.If you’re a small business owner who can’t afford a 50 member team, AI becomes your silent partner.
Not to replace people but to protect your energy, save time and let your people focus on what matters.
Chapter 4: How You Can Start — Right Here, Right Now
Now you might be thinking — “That’s great for them. But I’m not a billion-dollar startup.”
You don’t need billions to apply these lessons.
Start by asking:
• What 3 tasks am I repeating daily or weekly?
• Can I automate or delegate them using AI or no-code tools?
• Where do my customers experience the most friction?
A few simple ways to begin:
• Use WhatsApp chatbots for FAQs.
• Train an AI assistant to answer 80% of customer queries
• Set up auto-reminders for payment follow-ups
• Use AI tools to suggest pricing, write emails, or respond faster
• Use AI to auto-score leads or flag at-risk customers
• Use a tool like Notion AI or Airtable to manage projects and leads
• Use workflow tools (Make, Zapier, or Notion AI) to eliminate repetitive steps
You’re not replacing your people.
You’re giving them (and yourself) the space to grow.
Chapter 3: 3 Strategic Shifts You Can Learn From (The 3 Operating Pillars- Scale, Scope, Learning)
1️⃣ Scale → Serve More Without Working More
“There’s no way a human centric approval process could handle this volume,” said Ming Zeng, Alibaba’s Chief Strategy Officer.
Ant built the “3-1-0” system:
• 3 minutes to apply
• 1 second to approve
• 0 human involvement
No branch visit. No paperwork. No manual underwriting.
Instead of adding more staff, they made approvals algorithm-driven.
• Transaction history
• Partner credit ratings
• Communication behavior
• Risk scoring based on 3,000 variables
All- powered by AI scanning.
Use automation for common delays, payment reminders, onboarding steps, invoice tracking, etc.
2️⃣ Scope → One System, Many Solutions
Ant used the same user data to:
• Offer investments (Yu’e Bao)
• Approve small loans (MYbank)
• Process payments (Alipay)
AI allowed them to serve multiple customer needs with shared infrastructure and real time data.
Don’t add more tools. Find tools that do more with the same customer data : CRM + marketing + finance in one place.
3️⃣ Learning → Build Systems That Improve Automatically
Ant ran hundreds of powerful A/B experiments per day.
Every click, swipe, or behavior becomes a signal.
Each one fed its system to get smarter.
Even if you’re small, you can:
• Track where customers drop off
• Test different WhatsApp messages
• Ask ChatGPT to summarize customer queries to see patterns
The goal isn’t perfection.
It’s tiny feedback loops that teach you how to serve better.
Conclusion: You Don’t Need a Billion Users, You Just the Right AI-First Model
Ant Financial didn’t win because they had the most money.
They didn’t start with an army.
They started with a clear problem and used data + AI to remove friction, not people.
They built the most intelligent operating system, one that learned faster, adapted faster and scaled without burning out its people.
As an Indian MSME, you don’t need to be the next Ant.
But you can:
• Serve faster
• Trust smarter systems
• Reclaim your team’s time and energy
The future of your business doesn’t depend on how hard you work.
It depends on how well your systems work for you.
And the journey starts with a single question:
“What can I automate, so my people can elevate?”
Case Study on Netflix
Netflix Style AI Personalization for E-Commerce: Boost Sales & Conversions
What Netflix Knows About You And How E-Commerce Can Use the Same AI Tricks to Explode Sales
Netflix doesn’t care what you say you want. It watches what you do and it’s almost always right. It learned everything from your clicks, your pauses, your guilty pleasures at 2 AM. Now ask yourself: Why isn’t your E-Commerce site doing the same?
Here’s the thing: Netflix isn’t just showing you movies. It’s running one of the most sophisticated AI-powered content recommendation and consumer behavior engines on the planet. Behind every binge-worthy night is a masterclass in personalization, prediction, and psychological precision.
What’s shocking?
Most E-Commerce businesses still haven’t borrowed these techniques. Let’s change that.
Netflix Isn’t in the Entertainment Business, It’s in the Attention Business
Netflix’s product isn’t movies, It’s time. More specifically: your time.
To capture it, they’ve built a ruthless recommendation engine that runs on machine learning, deep neural networks and reinforcement learning. What that means is:
- Netflix doesn’t just suggest similar titles.
- It learns how long you hover.
- When you pause.
- What you skip.
- How likely you are to binge versus bounce.
- Even your decision fatigue patterns.
Now imagine applying that intelligence to an E-Commerce store:
- Knowing which product a customer will buy next (before they even browse).
- Designing homepages that adapt in real time to shopper moods.
- Eliminating “decision overwhelm” at checkout using behavioral AI.
This is Netflix logic, ready to be plugged into your business.
Inside Netflix’s AI Brain: Lessons You Can Steal
Here are 3 Netflix AI tactics that E-Commerce founders can apply today:
- Dynamic Personalization at Scale
What Netflix Does:
No two users see the same homepage. Not just in terms of titles, but in how they’re displayed. If a user responds better to action themed thumbnails over romantic ones, AI adapts the visuals.
How E-Commerce Can Use It:
Stop showing every customer the same hero banner or product grid. Use AI to detect user behavior and dynamically adapt:
- Images (product lifestyle vs. technical shots)
- Pricing formats (monthly vs. one-time)
- Language tone (urgent vs. informative)
You’re not just selling a product. You’re selling the right presentation of that product.
- Micro-Segmentation, Not Demographics
What Netflix Does:
Forget age, gender, or geography. Netflix groups users by watching behavior clusters like “impulse bingers” or “weekend explorers.”
How E-Commerce Can Use It:
Start clustering customers based on shopping behavior, not demographics. Use AI to identify micro-segments like:
- “Window Shoppers Who Need a Nudge”
- “Deal Hunters Who Convert with Scarcity”
- “Repeat Buyers Who Love Bundles”
Then tailor offers, retargeting and content to each type.
- AI-Driven Content Creation
What Netflix Does:
Ever wonder why Netflix makes its own shows? AI told them what genres and stars were trending before they produced hits like House of Cards and Stranger Things.
How eCommerce Can Use It:
Use generative AI to:
- Predict what product lines are likely to take off (based on trend analysis)
- Automatically generate product descriptions and A/B test them in real time
- Identify the ideal influencer to promote a specific SKU
You’re not just reacting to the market, you’re pre writing it.
The Big Takeaway: Don’t Copy Netflix’s Business. Copy Their Intelligence.
Netflix isn’t successful because of the content. It’s successful because of how it delivers the content.
E-Commerce is no different. You don’t need better products, you need smarter delivery.
That’s where AI gives you leverage.If you’re still relying on static funnels, generic emails and one size fits all storefronts, you’re leaving serious money on the table.
Netflix wouldn’t.